In a method for detecting obstacles for a rail vehicle, 3D sensor data is detected from a surrounding region, 3D image data is generated from the 3D sensor data, and 2D image data is generated on the basis of the 3D image data. A 2D anomaly mask is ascertained or generated by comparing the 2D image data with reference image data which is free of a collision obstacle. In the process, image regions are identified as mask regions in the 2D image data which differ from the corresponding image regions in the reference image data. By fusing the 2D anomaly mask with the 3D image data, a 3D anomaly mask is generated in the 3D image data. Finally, the 3D image data which is part of the 3D anomaly mask is interpreted as a possible collision obstacle. There is also described an obstacle detection device and a rail vehicle.


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    Title :

    Self-learning warning system for rail vehicles


    Contributors:
    SEMA ALBI (author)

    Publication date :

    2024-04-02


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    B61L Leiten des Eisenbahnverkehrs , GUIDING RAILWAY TRAFFIC / G06V



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